Abstract 2107: Development a customized panel with clinical application potential for transcriptome analyses in selected cancer types using FFPE specimens
Authors: Vittorio D'Urso, Dorothee Foernzler, Dennis O’Rourke, Danyi Wang, Jorge F Sanchez-Garcia, Heidi Giese, Thomas Clarke IV, XiaoZhe (Janet) Wang, Andreas Machl, Ti Cai, Juergen Scheuenpflug, Zheng Feng
Journal: Cancer Research (2023)

Abstract Purpose: HTG EdgeSeq is a Next Generation Sequencing (NGS) based RNA Sequencing (RNA Seq) platform using a quantitative nuclease protection chemistry that enables extraction-free quantitation of mRNA/miRNAs with significantly reduces FFPE sample requirements compared to standard RNA-Seq, which makes it a feasible option for potential clinical applications. A customized gene panel was designed and developed for detection gene signatures. Procedure: The customized gene panel consists of 1327 genes, including 900 genes in signaling pathways in oncology &amp; immuno-oncology, which including Nature Kill (NK) cells, neutrophils, Plasmacytoid dendritic cells (pDCs), DCs, monocytes, Tregs, B cells, tumor associated macrophages (TAMs), TGFβ, EMT, interferon-γ signature, IL-17, β-catenin etc. and 15 house-keeping genes. The validation included in silico probe design, feasibility testing, data comparison with The Cancer Genome Atlas (TCGA) and precision studies in six cancer indications including: Non-Small-Cell Lung Cancer (NSCLC), Head and Neck Squamous Cell Carcinoma (HNSCC), Hepatocellular Carcinoma (HCC), Colorectal Cancer (CRC), gastric cancer (OC), ovarian cancer (GC). Data Summary: After the In-silico probe design for all genes the custom probe pool for quality control test in biological samples was performed by evaluating directional and expected expression of 1327 selected genes in 59 FFPE samples from six indications. All probes performed as expected according to specification; gene expression signatures data were consistent with the different cancer indication tested. Expected differential expression of the selected genes was based on RNA-Seq data as reported in TCGA. In addition, principal component analysis (PCA) performed on the entire data et, showed a distinct clustering of samples by indication, demonstrating that the custom panel was able to reliably identify each indication. For the validation, precision studies including inter-well, inter-day, inter-processor, inter-sequencer and site-to-site comparisons were performed using FFPE tissue lysate pools prepared from each of the 6 indications. Predefined acceptance criteria are ≥ 90% of all Lin`s Concordance Correlation Coefficients (LCCC) comparisons to be greater than 0.90. The results showed that the predefined acceptance criteria were met, which are 95.9% of LCCC &amp;gt; 0.90 for inter-well repeatability, and 100% of LCCC &amp;gt;0.90 for inter-day, inter-processor, inter-sequencer and inter-site comparisons. Conclusions: The designed panel met all the predefined quality and analytical acceptance criteria, also, the reported results is corrected with TCGA RNA-Seq data, and the precision studies confirmed its performance. Customized gene panel can be possibly utilized for potential predictive and prognostic biomarkers identification to inform new cancer therapies development. Citation Format: Vittorio D'Urso, Dorothee Foernzler, Dennis O’Rourke, Danyi Wang, Jorge F Sanchez-Garcia, Heidi Giese, Thomas Clarke IV, XiaoZhe (Janet) Wang, Andreas Machl, Ti Cai, Juergen Scheuenpflug, Zheng Feng. Development a customized panel with clinical application potential for transcriptome analyses in selected cancer types using FFPE specimens [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2107.